Compressed Counting Meets Compressed Sensing [article]

Ping Li, Cun-Hui Zhang, Tong Zhang
2013 arXiv   pre-print
Compressed sensing (sparse signal recovery) has been a popular and important research topic in recent years. By observing that natural signals are often nonnegative, we propose a new framework for nonnegative signal recovery using Compressed Counting (CC). CC is a technique built on maximally-skewed p-stable random projections originally developed for data stream computations. Our recovery procedure is computationally very efficient in that it requires only one linear scan of the coordinates.
more » ... r analysis demonstrates that, when 00 and C=pi/2 when p=0.5. In particular, when p->0 the required number of measurements is essentially M=K\log N, where K is the number of nonzero coordinates of the signal.
arXiv:1310.1076v1 fatcat:h3zwjvimkzhs3a6hbwvmu2tuju